Business Innovation and Growth Support (BIGS)
Detailed information for 2019-2020
The purpose of this statistical program is to contribute, in collaboration with the Treasury Board Secretariat (TBS), to the improvement of performance and impact assessments for growth and innovation-related programs as announced in federal Budget 2018.
Data release - October 26, 2021
Federal departments and agencies will annually provide data on recipients of funding, grants and awards from their growth and innovation program streams for an annual horizontal review. The data received by federal departments will be linked to the Linkable File Environment (LFE) of Statistics Canada.
The Business Innovation and Growth Support (BIGS) database covers government activities that support business innovation and growth, such as funding, consulting services to enterprises, industry-facing research and development, support provided directly or in partnership, as well as support for technology development (commercialization) and exports. Fundamental science, tax expenditures, provincial and territorial programs, and Crown corporations of the Government of Canada were not included in the scope of this initiative.
Statistics Canada and the Treasury Board Secretariat are working closely together on various growth and innovation support related programs and initiatives which help to provide comprehensive, evidence-informed advice on innovation programming and policy.
Statistics Canada will lead the annual horizontal administrative data acquisition activities; will perform data linkage to the LFE; and will produce statistical outputs for the public and the Treasury Board Secretariat.
Reference period: The 12-month fiscal period between April 1st of the reference year and March 31st of the following year.
- Business performance and ownership
- Science and technology
- Small and medium-sized businesses
Data sources and methodology
All federal departments and agencies with growth support and innovation program streams.
Data collection for this reference period: 2020-11-09 to 2021-07-20
Data are extracted from administrative files.
Program stream information are acquired from federal departments and agencies. The data acquisition is based on a template filled in by agencies and federal departments. Then, the data received by Statistics Canada are treated and linked to the Linkable File Environment at the enterprise level.
The information acquired that is not aggregated at the enterprise level will be stored and maintained by the Centre of Special Business Projects (CSBP). This information will be extracted for customized demands for analytical and program evaluation purposes on a case by case depending on the data quality.
An enterprise is considered an ultimate beneficiary when it benefits from the activities of a program stream. Support provided to an ultimate beneficiary may come directly from a federal department or indirectly through an intermediary. For a given program stream, an intermediary cannot be an ultimate beneficiary. For example, ultimate beneficiaries may be for-profit or non-profit enterprises as well as government organizations or educational institutions.
The definition provided to departments for a transaction value used to derive the support value was: the total value of all transactions of the specific type in the reported annual period. Support can generally be classified as either financial or service-based.
Name of the administrative data source:
Business Innovation and Growth Support (BIGS).
The BIGS links program data from the federal departments and agencies to the Linkable File Environment (LFE). For more information on LFE see:
Section in the Statistics Act under which the data were obtained or if the data were considered to be available to the public:
The data is acquired under the authority of the Statistics Act.
The information will be shared with Statistics Canada for matching to the LFE, which will allow indicators of firm level performance to be developed for analysis. Only aggregated data will be published, after ensuring that confidential information on individual businesses cannot be identified in any of the data products that are developed for publication. Statistics Canada maintains robust information security practices and methods for ensuring confidentiality of private data. Statistics Canada will acquire data in accordance with the Statistics Act, the Privacy Act, and related regulations and Statistics Canada and Treasury Board policies.
Intended use of the administrative data for statistical purposes:
Tabular output, analysis, reports and database on the performance of federal innovation and growth support program streams.
Data processing conducted on the administrative data by the data provider and by Statistics Canada including making changes to adjust for differences in concepts and definitions:
The data provider send to Statistics Canada EXCEL spreadsheets with records of transactions for all innovation and growth support program streams.
Editing of the transactions was done in collaboration with the administrators of program streams and TBS subject matter personnel.
Approval to link the program stream data to the Linkable File Environment (LFE) (Record linkage approval 057-2017).
Transactions records were linked to the latest version of Business Register to obtain the Operating Entity Number of the recipients of the transactions. In cases where the Business number was provided, a deterministic match was performed. If there was no business number, a probabilistic match was done using information provided by the programs streams. A clerical review was done to remove false matches. No imputation was done.
For the users interested in analyzing at the enterprise level, a set of tables are produced using the enterprise as the statistical unit of observation. Any individual or unique enterprise could have multiple transactions and the transactions could be in multiple years. Data of interest from the Linkable File Environment was extracted for each matched enterprise to create a linked micro-dataset that was used to produce tabular estimates and econometric analysis.
Data editing was carried out in collaboration with the data providers at the transaction micro level. A manual review of all files received from the departments was carried out in order to identify errors as well as partial non-response. A list of questions as well as summary tables of the number of transactions and total amounts of support was produced. These questions and totals were sent to departments in order to get more precise information and confirmation of accuracy.
Following the integration of data into a central file, checks were carried out to identify partial non-response as well as inconsistencies with the specification of the data that had been provided by the departments. Data was then cleaned to standardize the data in order to be consistent with the specification of the data. Thus, data were treated in order to standardize the names of the programs and the dates of the transactions. Data from outside of the period of interest were deleted. When necessary, departments were contacted in order to get more details.
No imputation was done.
Subject matter experts from the Treasury Board Secretariat who are knowledgeable of the program streams are brought in to CSBP as "deemed employees" to assist Statistics Canada analysts in the validation of data acquired and selected tabular outputs that are produced.
After receiving the data, all departments were contacted to confirm the total amount of support received.
Tables were also compared with results from the horizontal innovation review conducted in 2017.
Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
G-Confid is used to protect confidential data.
Revisions and seasonal adjustment
Data are subject to revision.
The accuracy of the tabular estimates is measured by:
The match rate of the linkage of transactions to the Business Register.
This match rate is over 90%.
Other quality measures are available on demand. For instance:
- the percentage of program streams that delivered data of the total number of program streams on the list of program streams provided by the Treasury Board Secretariat;
-the comparison of total value of transactions delivered to the total value of successfully matched transactions;
-the number of missing data for variables of interest that were extracted from the Linkable File Environment.
Since each department has a legislated responsibility for the assessment of the administrative data provided on innovation-related support projects, the degree of integrity of data provided is considered acceptable.
Initial investigations are performed to ensure that all properties on the data file are unique. Duplicates records are identified and then suppressed.
Best efforts were made to clean up all microdata within the timeline of the project and a number of additional checks were applied to the data, as part of the LFE's quality assurance procedures. Moreover, data validation based on the subject-matter expertise of the TBS was also performed. Therefore, the quality of the data is deemed high. However, considering: the different objectives of individual programs and the related heterogeneity in the capture and classification of recipient data, without the benefit of using the data in rigorous and in-depth analytical work yet, the data will continue to be subject to validation.
As is the case with any new data set, and as subject-matter knowledge is gained with the move toward the establishment of an ongoing collection program, it is conceivable that revisions may become necessary. Data validation work will continue on several fronts, such as: improve the match rate, including through ongoing communication with individual organisations and programs; further use of detailed cross-sectional and time series data in analysis by subject-matter experts, and; ongoing statistical improvements in data sources, e.g. improved NAICS allocation of unclassified enterprises in the BR.
Year-over-year comparisons should be made with caution. Year-over-year differences in the number of enterprises and support values may be the result of changes in departmental financial systems and the unavailability of data rather than changes to the programs. Overall, data from the most recent years are of better quality and are more complete.